I came across this journal article a couple of years ago. It’s very accessible (not at all difficult to understand as journal articles go). It provides some interesting results that may help inform your decision about whether or not to use Excel and some background as to why we use dedicated statistical/computational software such as Matlab/Scilab/R.
The failings of Excel might seem like they only occur in extreme cases, but it is the way Excel handles the errors that is most concerning. In many of the examples listed in the article, it will return an incorrect value rather than admit that it doesn’t know the answer to that level of precision. I.e. when beyond the ability of the function, Excel should return NAs.
The last paragraph:
“Finally, as a rule of the thumb, every user should be aware that spreadsheets have serious limitations. Other platforms are advisable, being currently R the most dependable FLOSS (Free/Libre Open Source Software, see Almiron et al. 2009).”
Almiron, M. G., Lopes, B., Oliveira, A. L. C., Medeiros, A. C., and Frery, A. C. (2010). On the numerical accuracy of spreadsheets. Journal of Statistical Software, 34(4):1–29.